Articles, advertisements, software, files, apps, and other information and content items are often published (i.e., made accessible to others) on a computer network for access by users of computers communicatively connected to the network. User access or interaction with a respective article has at times been monitored to measure indications of user activity and interest in the item. User activity and interest as to any particular individual item has typically been monitored and measured only as to the specific, individual item.
Certain analytics applications, such as web analytics, have collected data related to a particular website or website feature. As an example, Google™ Analytics has provided summarized “dashboard” metrics profiling use of a particular website searchable through the Google™ Internet directory search service, including summarized metrics such as website visits, bounce rate, average time on site, referring or direct hits, and similar information regarding a particular website of the service. Other web analytics providers, such as Facebook™ Insights, have made available summarized metrics profiling a particular social network “Page” of the service, including summarized metrics such as numbers of posts to the Page, total “Likes” by others relating to Page contents, and numbers of posters for content associated with the Page contents. Other publicly available and private sources make available similar and other types of summarized metrics, for individual websites, pages, blogs, and the like.
Though conventional analytics have provided various website, website page and website feature metrics, the conventional analytics do not directly provide insight into particular topical contents or subjects of the websites, pages, or features. Of course, topical content may be contained or addressed in any website, page, blog or the like, such as in articles, links, software programs, advertisements, social media text, and others. Because conventional analytics and schemes have been directed to visit and traffic measurement of individual websites and pages, measurement of the popularity and attention to an idea, theme, or topic related to a shared or published object or item has not been possible. Such measurements of popularity and attention to an idea, theme or topic, however, would significantly benefit businesses and persons interested in more holistic measure of topical awareness/interest (as opposed to the conventional analytics focus on measures associated only with visits, traffic types or location, and similar individualized aspects for an individual website, page or similar item).
The summarized metrics available from conventional analytics provide overview measurement of the activity in the computer network system. Identification of the individual actors (e.g., the communication devices and users of those devices) contributing to activity in the computer network system may be available from the system. The social networking site Twitter™, for example, provides an application programming interface (API) call that can return identifications of the individual actors in the social network system. The individual actors can be identified, for example, by username or user handle associated with the communications device and corresponding to its user. Although identification of individual actors is possible, the identification, itself, has not had relevance to particular ideas, themes and topics relevant to those individual actors.
It would, therefore, be a significant improvement in the art and technology to provide for topical activity monitoring for measure of user activity and interest in particular topic or category of articles generally, and for targeting particular identities corresponding devices communicatively contributing to topical activity in a computer network system.